What is he best known for?
The fields of study he is best known for:
- Programming language
- Algorithm
- Algebra
Sebastiano Vigna spends much of his time researching Theoretical computer science, Graph, World Wide Web, Discrete mathematics and Information retrieval.
His Theoretical computer science research is multidisciplinary, incorporating elements of Webgraph, Data structure and Complex network.
Sebastiano Vigna combines subjects such as Query expansion, Web query classification, Applied mathematics, Query optimization and Function with his study of Graph.
His Metadata study in the realm of World Wide Web interacts with subjects such as Friendship, Milgram experiment and Probabilistic analysis of algorithms.
His Discrete mathematics research focuses on Combinatorics and how it relates to Social network analysis.
His work in Information retrieval addresses issues such as Graph, which are connected to fields such as Control flow graph, Query language, Search engine and Web search query.
His most cited work include:
- The webgraph framework I: compression techniques (917 citations)
- UbiCrawler: a scalable fully distributed web crawler (477 citations)
- Layered label propagation: a multiresolution coordinate-free ordering for compressing social networks (422 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Theoretical computer science, Discrete mathematics, Combinatorics, Algorithm and Graph.
His Theoretical computer science research includes elements of Computation and Social network.
His work carried out in the field of Discrete mathematics brings together such families of science as Class, Trie, Arithmetic and Turing machine.
His study on Cayley graph, Degree and Graph theory is often connected to Sense of direction and Regular graph as part of broader study in Combinatorics.
His Algorithm research is multidisciplinary, relying on both Simple, String, Set and Data structure.
Sebastiano Vigna studies Webgraph which is a part of Graph.
He most often published in these fields:
- Theoretical computer science (28.57%)
- Discrete mathematics (22.36%)
- Combinatorics (20.50%)
What were the highlights of his more recent work (between 2013-2020)?
- Algorithm (14.91%)
- Data structure (9.32%)
- Perfect hash function (6.83%)
In recent papers he was focusing on the following fields of study:
Sebastiano Vigna mainly investigates Algorithm, Data structure, Perfect hash function, Pseudorandom number generator and Combinatorics.
His Algorithm research includes themes of Linear system and Set.
His Pseudorandom number generator study combines topics in areas such as Discrete mathematics, Multiplication, Arithmetic and State space.
His work in Combinatorics covers topics such as Monotonic function which are related to areas like Monotone polygon.
His studies in Fenwick tree integrate themes in fields like Ranking and Theoretical computer science.
His work deals with themes such as Social graph and Antichain, which intersect with Theoretical computer science.
Between 2013 and 2020, his most popular works were:
- Axioms for Centrality (254 citations)
- Graph structure in the web --- revisited: a trick of the heavy tail (75 citations)
- Toward Reproducible Baselines: The Open-Source IR Reproducibility Challenge (65 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Algorithm
- Algebra
His primary areas of investigation include World Wide Web, Crawling, Web crawler, Graph and Statistical hypothesis testing.
Sebastiano Vigna interconnects Open source, Data science and Code in the investigation of issues within World Wide Web.
The Graph study combines topics in areas such as Strongly connected component, Heavy-tailed distribution, Web page and Giant component.
His Heavy-tailed distribution research integrates issues from Ranking, Theoretical computer science and Web mining.
His study in Set extends to Theoretical computer science with its themes.
His Statistical hypothesis testing research is multidisciplinary, relying on both State space, Xorshift, Pseudorandom number generator, Constant and Multiplication.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
